China's Outward Foreign Direct Investment Patterns: Evidence from Asian Financial Markets

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Print ISSN: 2288-4637 / Online ISSN 2288-4645 doi: 10.13106/jafeb.2020.vol7.no2.157

China’s Outward Foreign Direct Investment Patterns:

Evidence from Asian Financial Markets

Yugang HE^*, Baek-Ryul CHOI^**

Received: October 03, 2019 Revised: October 13, 2019 Accepted: November 30, 2019

Abstract

Since the economic crisis sweeps across the world in 2008, the foreign direct investment of various countries has been greatly impacted.

Therefore, this paper regards China as an example to analyze China’s outward foreign direct investment patterns in terms of Asian financial markets with a panel data over the period 2003-2017. We mainly focus on the money market oriented outward foreign direct investment and foreign exchange market oriented outward foreign direct investment. Using the individual fixed effect model to conduct empirical analyses, the empirical findings indicate that China will reduce its foreign direct investment amount to a country with large money supply and China will increase its foreign direct investment amount to a country with large foreign exchange reserves. Furthermore, when a country has signed Free Trade Agreement with China, China will increase more foreign direct investment amount to these countries than that of a country who has not signed Free Trade Agreement with China. Moreover, the empirical findings indicate that no matter what the money market oriented outward foreign direct investment or foreign market oriented outward foreign direct investment, China will reduce its foreign direct investment amount to these Asian countries due to the global economic crisis.

Keywords: Outward Foreign Direct Investment Patterns, Asian Financial Markets, Global Economic Crisis, Individual Fixed Effect Model, Free Trade Agreement

JEL Classification Code: C33, C36, F00, G00.

1. Introduction 1²

As the largest developing country, China is the second largest economic entity in the world. In recent years, with the rapid improvement of science and technology, China's domestic output has increased substantially. Domestic demand has been greatly met, and there has been a large amount of excess capital. For the rational use of excess capital, the Chinese government has issued a number of policies, such as the Building-up of Asian Infrastructure Investment Bank and the implementation of "One Belt and One Road" to transfer excess domestic capital to foreign countries. Meanwhile, the deepening of Reform and Opening-up Policy also creates favorable policy support for

* First Author, Doctoral Student, Department of International Trade, Jeonbuk National University, Korea.

Email: [email protected]

* * Corresponding Author, Professor, Department of International Trade, Jeonbuk National University, Korea.

Email: [email protected]

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non- Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non- commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Chinese enterprises to invest overseas. On September 28, 2018, the National Bureau of Statistics and State Administration of Foreign Exchange of China and the Ministry of Commerce have jointly issued the “2017 Statistical Bulletin of China’s Outward Foreign Direct Investment”. As this report indicates, China's outward foreign direct investment in 2017 amounts to $158.29 billion. Compared with that in 2016, China has experienced negative growth which does not happen before since the annual statistics are released in 2003, but it is still the second highest in history. Moreover, it accounts for more than 10% of the global share for two consecutive years.

Because the influence of China's outward foreign direct investment is expanding, the scale of China's outward foreign direct investment has been the third largest in the world and lags behind that of the United States and Japan.

In recent years, with the increase of global uncertainties, the patterns and scales of outward foreign direct investment in each country will be greatly affected. Therefore, this paper uses China as an example to exploit China’s outward foreign direct investment patterns in terms of Asian financial markets with a panel data over the period from 2003 to 2017. According to the general international

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standards, financial markets can be divided into capital market, money market, gold market and foreign exchange market. This paper mainly concentrates on the impact of external factor from target countries’ money market and foreign exchange market on China’s outward foreign direct investment patterns. Stated differently, we will mainly take the money market oriented outward foreign direct investment and the foreign exchange market oriented outward foreign direct investment. Moreover, with the deepening of economic globalization, China have signed the Free Trade Agreement with many Asian countries to serve for international economic cooperation.

This kind of economic behavior may affect China’s outward foreign direct investment patterns to Asian countries. Due to this reason, two dummy variables are set to solve the problem from the Free Trade Agreement.

Furthermore, the global economic crisis happened in 2008 as a representative of global economic uncertainty is taken into consideration. We set a dummy variable about the global economic crisis to examine the changes of China's outward foreign direct investment patterns to Asian countries before and after the global economic crisis. Using the individual fixed effect model to conduct empirical analyses, we have come to four findings: First, when a country has a large amount of money supply, China will reduce its foreign direct investment amount to that country.

Second, when a country has a large number of foreign exchange reserves, China will increase its foreign direct investment amount to that country. Third, when a country has signed the Free Trade Agreement with China, this country will receive more China’s foreign direct investment amount than that of a country has not signed the Free Trade Agreement with China. Finally, no matter what the money market oriented outward foreign direct investment or the foreign market oriented outward foreign direct investment, China will reduce its foreign direct investment amount to these target Asian countries due to the global economic crisis.

To this end, the rest of this study will be formed as follows: Chapter two will analyze the literature review.

Chapter three will present the theoretical framework.

Chapter four will present the results. Chapter five will present the conclusion.

2. Literature Review

Actually, there are many literature involving China's foreign direct investment. The main purpose of this chapter is to collate and summarize the previous relevant literature.

Then, by comparing these documents, we will show the innovation of this paper. In general, the determinants of foreign direct investment can be divided into two

categories. One is the internal determinants such as domestic economic growth and domestic employment.

Another is the external determinants such as investment target country’s interest rate and inflation.

As for the internal determinants, Lee (2010) takes use of Japan’s data to analyze the effect of economic growth on outward foreign direct investment within the Granger causality framework. His finding demonstrates that there is a long-run positive one-way causal relationship between outward foreign direct investment and GDP per capita.

However, this kind of relationship does not exist in the short run. Chen and Zulkifli (2012) set Malaysia over the period from 1980 to 2010 as a sample to explore the association between OFDI and economic growth using the multivariate framework. Using the vector error correction model, their findings indicate that a long-run positive relationship between economic growth and OFDI exists.

Meanwhile, the result of causality shows that there is a two-way causality between both of them in the long run.

But, in the short run, they do not find the Granger causality between economic growth and outward foreign direct investment. Wang, Cheng, Wang, and Li (2014) employ the dynamic threshold model to discuss the effect of economic growth (it is replaced by the institutional quality) on outward foreign direct investment with a sample of 73 countries over the period of 2000 to 20008. They find that the economic growth has a strong effect on outward foreign direct investment only when the institutional quality is within a certain range. However, the low institutional quality which is accompanied by the low economic development will not promote the outward foreign direct investment significantly.

Wei, Alon, and Ni (2012) attempt to explore the home country’s macroeconomic determinants on China’s outward foreign direct investment. They find that the foreign exchange reserves have a positive effect on China’s OFDI. In terms of foreign exchange market, He (2018) set china as an example to exploit the effect of macroeconomic variables on China’s OFDI to Japan. Using vector error correction model to conduct empirical analyses, he finds that the real exchange rate is positively associated with China’s OFDI to Japan. However, the real exchange rate volatility, trade openness and real GDP are negatively related to China’s OFDI to Japan. In terms of money market. Patel and Mah (2018) employ the time series data over period from 1980 to 2015 with a sample of South Africa. Based on estimation of vector error correction model, they also find that the money supply is negatively related to the OFDI.

As for the external determinants, Chou, Chen, and Mai (2011) use the spatial econometric model to investigate the influence of economic integration on China's outward foreign direct investment. They find that the political risks

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of host countries have a negative impact on China's OFDI.

The similarity with Chinese Culture and GDP per capita of host countries are positively related with China's outward foreign direct investment. Moreover, the market opportunities of the host countries have a significant negative impact on China's outward foreign direct investment. Blomkvist and Drogendijk (2013) attempt to analyze the impact of psychic distance and its individual stimuli (differences in geographic distance, language, economic development, religion, culture and political systems, education) on China’s outward foreign direct investment. Using the ordinary least squares to conduct empirical analyses, they find that its stimuli and the psychic distance can not be left out as explanatory factors for Chinese outward foreign direct investment.

Lee and Zhai (2013) and Kang and Kim (2014) use different samples to analyze this proposition and obtain the same conclusions. Bhasin and Jain (2015) explore the role of host country factors in attracting India's outward foreign direct investment by using panel data of 15 host countries over the period from 2000 to 2009. they find that the technology, bilateral investment treaties and the opening up of host countries are important determinants of India's outward foreign direct investment. Li, Huang and Dong (2019) adopt the panel smooth transition regression model to study the nonlinear effects of outward foreign direct investment in 12 “One Belt and One Road” countries over the period from 2010 to 2015. They find that both overall economic freedom, the interaction of economic freedom and patent, bilateral trade, GDP and institutional instance significantly influence the outward foreign direct investment. Moreover, they also find that economic freedom and economic development have the inverted “U”

effect on outward foreign direct investment in the different regime.

The above literature analyses the impact of internal and external factors on outward foreign direct investment.

Compared with these literature, this paper sets China as an example to analyze China’s outward foreign direct investment patterns in terms of Asian financial markets (money market and foreign exchange market) with a panel data over the period from 2003 to 2017. It is also the innovation of this paper to find out the influencing factors of outward foreign direct investment from the financial markets.

3. Theoretical Framework 3.1. Model Specification

Generally speaking, there are two main factors affecting the outward foreign direct investment (OFDI) patterns. One

is the internal factor (factors of home country affecting the outward foreign direct investment to target country). Yan, Zhang, Shen and Han (2018) attempt to explore the link between productivity, financial constraints and outward foreign direct investment with firm-level evidence. As internal factors, they find that both financial constraints and productivity are important factors which can affect firm’s ability to perform the outward foreign direct investment.

Wei, Zheng, Liu and Lu (2014) also perform a research about internal factors that expand to the outward foreign direct investment. They find that national and sub-national institutions, export experience, productivity, capability and entry barriers affect the outward foreign direct investment decisions. The other is the external factor (factors of target countries affecting the outward foreign direct investment patterns of home country). Liu, Ge, Hu and Wang (2018) try to explore the spatial differentiation of China’s OFDI.

As external factors, they find that the U-shaped curve relationship between cultural distance and China's outward foreign direct investment exists. Furthermore, their findings indicate that China's OFDI does not merely flow to similar cultural economy. Clegg, Lin, Voss, Yen and Shih (2016) employ panel data of 4619 observations from 261 Chinese publicly listed firms from 1991 to 2011 to analyze factors that may affect the outward foreign direct investment patterns. They find that the host-country risk is an important factor for a home country to conduct the outward foreign direct investment to the host-country. Yoo (2016) analyze this proposition in terms of ASEAN countries. He finds that ASEAN FTA is not effective to attract FDI.

Compared with others, in this paper, we try to explore the external factor from target countries’ financial markets.

According to the general international standards, financial markets can be divided into gold market, capital market, money market and foreign exchange market and. This paper mainly concentrates on the impact of external factor from target countries’ money market and foreign exchange market on China’s outward foreign direct investment patterns. Due to that there are a lot of indexes to measure the target countries’ money market and foreign exchange market, in this paper, the money market oriented outward foreign direct investment is represented by the money supply of each target country. Foreign exchange market oriented outward foreign direct investment is represented by the foreign exchange reserve of each target country.

Moreover, as the market size and productivity of target countries are two important factors affecting China's OFDI patterns, both of them are taken into account in this paper.

The basic estimated equation gives:

t i t i t j t

j

t j t

j t

j i

gdppc a

gdp a

exchange a

money a

a ofdi

, ,

4 , 3

, 2

, 1

0 , ,

log log

log





  



 (1)

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Where i represents China. t represents the year. j represents the target country. ofdi represents China’s foreign direct investment amount to each target country.

money represents the money supply of each target country.

exchange represents the foreign exchange reserve of each target country. gdp represents the GDP of each target country. gdppc represents the GDP per capita of each target country. _i represents the individual effect.

t represents the time effect. _i,_t represents the white noise. logrepresents logarithmic value of each variable.

Since the impact of Free Trade Agreement (FTA) on China's outward foreign direct investment patterns can not be ignored, this paper estimates China's outward foreign direct investment patterns between countries who have signed FTA with China and those who have not signed FTA with China, respectively. Using dummy variables and mutual variable to conduct empirical analysis, we can compare elastic coefficients of different countries. The estimated equation about the money market oriented outward foreign direct investment give:

t i t i t j m

t j m

t j t

j

t j t

j t

j i

gdppc fta

gdp fta

money fta

gdppc gdp

exchange money

ofdi

, ,

7

, 6

, 5

, 4

, 3

, 2

, 1

0 , ,

log

log log

log

























(2) Where fta_m represents the countries that have signed

FTA with China (money market oriented outward foreign direct investment). If a country has signed FTA with China, the value will be one. Otherwise, zero. ₁ represents the coefficient of money market oriented outward foreign direct investment amount (countries that have not signed FTA with China). The sum of ₁ and ₅represents the coefficient of money market oriented outward foreign direct investment amount (countries that have signed FTA with China). ₀ represents the constant. _₂, ₃, _₄,

6and ₇ are coefficients of variables, respectively.

Then, the estimated equation about the foreign exchange market oriented outward foreign direct investment give:

t i t i t j e

t j e

t j t

j t

j

t j t

j i

gdppc fta

gdp fta

exchange fta

gdppc gdp

exchange

money ofdi

, ,

7

, 6

, 5

, 4

, 3

, 2

, 1

0 , ,

log

log log

log

log log

























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Where fta_e represents the countries that have signed FTA with China (foreign exchange market oriented outward foreign direct investment). If a country has signed FTA with China, the value will be one. Otherwise, zero.

2 represents the coefficient of foreign exchange market oriented outward foreign direct investment amount (countries that have not signed FTA with China). The sum of ₂ and ₅ represents the coefficient of foreign exchange market oriented outward foreign direct investment amount (countries that have signed FTA with China). ₀ represents the constant. ₁, ₃, ₄, ₆ and

7 are coefficients of variables, respectively.

Furthermore, due to that the global economic crisis happened in 2008 may have a great impact on China’s OFDI patterns, we will set a dummy variable about the global economic crisis (d₂₀₀₈). If the year before 2008, the value of d₂₀₀₈ will be zero. And if the year after 2008, the value of d₂₀₀₈ will be one. The estimated equation (in terms of money market oriented outward foreign direct investment) about the global economic crisis gives:

t i t i t j

t j t

j

t j t

j

t j t

j t

j i

gdppc d

gdp d

money d

gdppc gdp

exhange money

ofdi

, ,

2008 7

, 2008

6 , 2008

5

, 4

, 3

, 2

, 1

0 , ,

log

log log

log

























(4) Where ₀ represents the constant. ₁ represents the coefficient of money market oriented outward foreign direct investment before 2008. The sum of ₁ and ₅

represents the coefficient of money market oriented outward foreign direct investment after 2008. ₂ ₃, ₄,

6 and ₇ are coefficients of variables, respectively.

Then, the estimated equation (in terms of foreign exchange market oriented outward foreign direct investment) about the global economic crisis gives:

t i t i t j

t j t

j t j t

j

t j t

j t

j i

gdppc d

gdp d

exchange d

gdppc gdp

exhange money

ofdi

, ,

2008 7

, 2008

6 , 2008

5

, 4

, 3

, 2

, 1

0 , ,

log

log log

log

























(5)

Where ₀ represents the constant. _₂ represents the coefficient of foreign exchange market oriented outward foreign direct investment before 2008. the sum of ₂ and

5 represents the coefficient of foreign exchange market oriented outward foreign direct investment after 2008. ₁

3, ₄ , ₆ and ₇ are coefficients of variables, respectively. From equation (1) to equation (5), all these equations will be employed to conduct empirical analyses one by one.

3.2. Variable Description

The flow of OFDI amount from China to each Asian country is treated as a dependent variable. It is sourced from “2017 Statistical Bulletin of China’s Outward Foreign Direct Investment” over period 2003 to 2017. The money supply and foreign exchange reserve are treated as core independent variables. They are collected from International Monetary Fund (International Finance Statistics) over period of 2003 to 2017. The GDP and GDP per capita are treated as control independent variables.

They are obtained from World Bank Open Data over period 2003 to 2017. These countries that have signed Free Trade Agreement with China are gained from China Free Trade Area Service Network. Those variables used in this paper will be exhibited in <Table 1>.

Table 1: Variable Description

Variable Type Abbreviation Definition Source

Dependent

Variable ofdi Flow of outward foreign direct investment (OFDI) amount from China to each Asian country

2017 Statistical Bulletin of China’s Outward Foreign Direct Investment

Independent Variable

money Money supply of each Asian country International Monetary Fund (International Finance Statistics) exchange Foreign exchange reserve of each Asian country International Monetary Fund

(International Finance Statistics)

gdp GDP of each Asian country World Bank Open Data

gdppc GDP per capita of each Asian country World Bank Open Data

Dummy Variable

d2008 Global economic crisis (before 2008, d₂₀₀₈=0; After 2008, d₂₀₀₈=1.)

ftam Money market oriented outward foreign direct investment (Those countries that have signed FTA with China, the value

will be one. Otherwise, zero.)

China Free Trade Area Service Network (http://fta.mofcom.gov.cn)

ftae

Foreign exchange market

Oriented outward foreign direct investment (Those countries that have signed FTA with China, the value will be

one. Otherwise, zero.)

China Free Trade Area Service Network (http://fta.mofcom.gov.cn)

4. Results

4.1. Data Description and Target Countries This paper includes one dependent variable (OFDI), four independent variables (money supply, foreign exchange reserve, GDP and GDP per capita) and three dummy

variables (global economic crisis, FTA in terms money market and FTA in terms of foreign exchange market). The basic statistics of these variables are presented in <Table 2>. Moreover, due to the availability of data, only 27 Asian countries are selected in this paper. Those Asian countries (target country) are employed are shown in <Table 3>.

Table 2: Data Description Variable

ofdi

log logmoney logexchange loggdp loggdppc

Statistic

Mean 2.569 3.305 1.387 3.750 2.047

Median 2.697 3.181 1.420 3.751 2.193

Maximum 5.019 6.891 3.113 4.800 3.793

Minimum -1.000 -1.181 -1.069 2.688 0.033

Std. Dve 1.107 1.625 0.908 0.679 0.790

Observation 331 331 331 331 331

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Table 3: Target Countries

Number Abb Number Abb

1 BRN 15 KAZ

2 PHL 16 KGZ

3 KOR 17 QAT

4 KHM 18 LBN

5 MYS 19 BGD

6 THA 20 JPN

7 SGP 21 NPL

8 VNM 22 TJK

9 ARE 23 LKA

10 OMN 24 SAU

11 PAK 25 TUR

12 BHR 26 ISR

13 JOR 27 IND

14 TLS

Note: Abb indicates the abbreviation of each country’s name

4.2. Money Market Oriented Outward Foreign Direct Investment

As well known, an increase in the money supply will arise a country’s inflation. According to Fisher effect, an increase in the inflation will lower the real interest of a country. Therefore, when foreign countries invest to that country, their earnings will be reduced. Then, foreign countries will reduce the foreign direct investment account to that country. Namely, the money supply has a negative effect on FDI from other countries. Before conducting empirical analyses, we perform Hausaman tests to decide

which effect is proper between random effect and fixed effect. Referring to the relevant statistics of Hausaman tests, we find that the individual fixed effect is more suitable.

The estimated results of money market oriented outward foreign direct investment are shown in <Table 4>.

Table 4 presents the estimated results of money m arket oriented outward foreign direct Investment. In m odel (4), it can been found that the coefficients of

money

log and fta_mlogmoneyget through the signifi cant test at 10% level. This indicates that an increase in money supply of a country who has not signed FT A with China will reduce China’s foreign direct invest ment to that country. When the money supply increase s by 1%, China’s foreign direct investment to that cou ntry will be reduced by 0.378%. Meanwhile, an increa se in the money supply of a country who has signed FTA with China will also reduce China’s foreign direc t investment to that country. When the money supply increases by 1%, China’s foreign direct investment to that country will be reduced by 0.183% (-0.378%+0.19 5%=-0.183%). Therefore, we can conclude that in term s of money market oriented outward foreign direct Inv estment, a country who has signed FTA with China w ill receive more foreign direct Investment amount from China than that of a country who has not signed FTA with China.

Table 4: Results of Money Market Oriented Outward Foreign Direct Investment

Dependent Variable logofdi

Model Model

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Model (2)

Model (3)

Model Independent Variable (4)

gdp

log ^1.566***_(0.575) ^1.557**_(0.685) ^1.571**_(0.780) ^1.556**_(0.776)

gdppc

log ^1.567**_(0.785) _(0.818)^1.549* _(0.833)^1.497* _(0.907)^1.377

money

log ^-0.351**_(0.128) _(0.231)^-0.354 _(0.229)^-0.350 ^-0.378*_(0.232)

exchange

log ^0.704**_(0.326) _(0.367)^0.703* _(0.426)^0.703 ^0.709**_(0.326)

gdp

fta_mlog ^0.031**_(0.013)

gdppc

fta_mlog _(0.927)^-0.111

money

fta_mlog _(0.122)^0.195*

constant -8.647***

(2.169)

-8.595***

(2.255)

-8.628***

(2.178)

-8.925***

(2.213)

Hausaman Test （4² ）^=134.682

(P-value=0.00)

（5² ）

 ^=147.910 (P-value=0.00)

（5² ）

 ^=152.373 (P-value=0.00)

（5² ）

 ^=150.592 (P-value=0.00)

Individual Fixed Effects Country Country Country Country

Adjusted R-squared 0.774 0.774 0.773 0.774

F-statistic 38.803 37.427 37.428 37.491

Prob (F-statistic) 0.000 0.000 0.000 0.000

Observation 331 331 331 331

Note: * represents 10% significant level. ** represents 5% significant level. ***1% represents significant level. () represents the value of standard error.

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4.3. Foreign Exchange Market Oriented Outward Foreign Direct Investment

Foreign exchange reserves can be used to deal with domestic economic turmoil. This will affect investors' confidence in performing foreign direct investments. If a country with a lot of foreign exchange reserves, this will bring a sense of security to investors. Then, investors will be willing to invest more to a country with large foreign exchange reserves. Stated differently, the foreign exchange reserve is positively related to the foreign direct investment.

Before conducting empirical analyses, we perform Hausaman tests to decide which effect is proper between random effect and fixed effect. Referring to the relevant statistics of Hausaman tests, we find that the individual fixed effect is more suitable. The estimated results of foreign exchange market oriented outward foreign direct investment are shown in <Table 5>.

Table 5 presents the estimated results of foreign exchange market oriented outward foreign direct Investment. We will mainly focus on model (8). It can be

found that both the coefficients of logexchange and exchange

fta_elog get through the significant test 5%

level. This means that an increase in the foreign exchange reserve of a country who has not signed FTA with China will increase China’s foreign direct investment amount to that country. When the foreign exchange reserve increases by 1%, China’s foreign direct investment amount to that country will be increased by 0.668%. At the same time, an increase in the foreign exchange reserve of a country who has signed FTA with China will also increase China’s foreign direct investment amount to that country. When the foreign exchange reserve increases by 1%, China’s foreign direct investment amount to that country will be increased by 0.789% (0.668%+0.121%=-0.789%). Therefore, we can summarize that in terms of foreign exchange market oriented outward foreign direct investment, a country who has signed FTA with China will receive more foreign direct Investment amount from China than that of a country who has not signed FTA with China.

Table 5: Results of Foreign Exchange Market Oriented Outward Foreign Direct Investment

Dependent Variable ofdi

Model Model

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Model (6)

Model (7)

Model (8) Independent Variable

gdp

log ^1.566***_(0.575) ^1.557**_(0.685) ^1.571**_(0.780) ^1.570**_(0.676)

gdppc

log ^1.567**_(0.785) _(0.818)^1.549* _(0.833)^1.497* ^1.496**_(0.702)

money

log ^-0.351**_(0.128) _(0.231)^-0.354 _(0.229)^-0.350 ^-0.361*_(0.230)

exchange

log ^0.704**_(0.326) _(0.367)^0.703* _(0.426)^0.703 ^0.668**_(0.339)

gdp

fta_elog ^0.031**_(0.013)

gdppc

fta_elog _(0.927)^-0.111

exchange

fta_elog ^0.121**_(0.056)

constant -8.647***

(2.169)

-8.595***

(2.255)

-8.628***

(2.178)

-8.442***

(2.214)

Hausaman Test （4² ）^=134.682

(P-value=0.00)

）

（²5

 ^=147.910 (P-value=0.00)

）

（²5

 ^=152.373 (P-value=0.00)

（5² ）

 ^=149.293 (P-value=0.00)

F-statistic 38.803 37.427 37.428 37.461

Prob (F-statistic) 0.000 0.000 0.000 0.000

Note: * represents 10% significant level. ** represents 5% significant level. ***1% represents significant level. () represents the standard errors.

When taking model (4) in <Table 4> and model (8) in

<Table 5> into consideration, it can be known the difference between a country who has signed FTA with China and a country who has not signed FTA in terms of money market and foreign exchange market. Stated specifically, a country who has signed FTA with China will

receive more foreign direct investment amount from China than that of a country who has not signed FTA with China.

4.4. Robustness Test

Due to that independent variables such as the money

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supply, foreign exchange reserve, GDP and GDP per capita

can be influenced by the outward foreign direct investment, the estimated results in <Table 4> and <Table 5> may be biased.

Table 6: PGMM Estimated Result of Money Market Oriented Outward Foreign Direct Investment

Model Model

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Model (10)

Model (11)

Model (12) Independent Variable

gdp

log ^1.002**_(0.426) _(0.589)^0.762 ^1.182**_(0.485) ^0.963**_(0.461)

gdppc

log _(0.195)^0.176 _(0.196)^-0.536 _(0.191)^0.343* ^0.315**_(0.159)

money

log ^-0.706**_(0.289) ^-0.814***_(0.268) ^-0.484*_(0.274) ^-0.555*_(0.354)

exchange

log ^0.612**_(0.266) ^0.704***_(0.256) _(0.247)^0.342 _(0.299)^0.582*

gdp

fta_mlog ^1.336***_(0.266)

gdppc

fta_mlog ^-3.967***_(0.295)

money

fta_mlog _(0.145)^0.225*

constant 1.890

(5.959)

4.197 (8.361)

2.481 (6.137)

1.320 (7.584)

J-statistic 16.911 15.611 16.114 16.927

P-value 0.391 0.408 0.374 0.323

Instrumental Variable gdp_t_-_n, gdppc_t__n, money_t__n, exchange_t__n, exchange_t__n, Constant

Note: * represents 10% significant level. ** represents 5% significant level. ***1% represents significant level. () represents the standard errors. n

is equal to 1, 2 ,3 and 4.

Table 7: PGMM Estimated Result of Foreign Exchange Market Oriented Outward Foreign Direct Investment

Model Model (13) Model (14) Model (15) Model (16)

Independent Variable gdp

log ^1.002**_(0.426) _(0.589)^0.762 ^1.182**_(0.485) ^1.075**_(0.468)

gdppc

log _(0.195)^0.176 _(0.196)^-0.536 _(0.191)^0.343* ^0.443***_(0.126)

money

log ^-0.706**_(0.289) ^-0.814***_(0.268) ^-0.484*_(0.274) ^-0.806***_(0.296)

exchange

log ^0.612**_(0.266) ^0.704***_(0.256) _(0.247)^0.342 _(0.273)^0.514*

gdp

fta_elog ^1.336***_(0.266)

gdppc

fta_elog ^-3.967***_(0.295)

exchange

fta_elog ^0.434***_(0.135)

constant 1.890

(5.959)

4.197 (8.361)

2.481 (6.137)

2.464 (6.318)

J-statistic 16.911 15.611 16.114 16.239

P-value 0.391 0.408 0.374 0.366

Instrumental Variable gdp_t_-_n^, gdppc_t__n^, money_t__n^,exchange_t__n, Constant

Note: * represents 10% significant level. ** represents 5% significant level. ***1% represents significant level. () represents the standard errors. n

is equal to 1, 2 ,3 and 4.